With the release of the “First Report and Order,” Feb. 14, 2002, by the Federal Communications Commission (FCC), interest in ultra wide bandwidth (UWB) communication systems has increased. The IEEE 802.15 standards organization, which is responsible for Personal Area Networks, has established a task group, TG3a, to standardize a high-data-rate physical layer based on UWB.
Ultra wide bandwidth (UWB) communication systems transmit and receive extremely short electromagnetic energy impulses, therefore the terms “UWB” and “impulse radio” are used synonymously herein. Because the bandwidth of the pulses is much wider than the bandwidth of the payload signal, UWB is a form of spread-spectrum communication. Each pulse can cover anywhere from 500 MHz to several GHz of the radio spectrum.
Information is transmitted by modulating the frequency, timing, amplitude, polarity, or other aspect of the pulses. UWB systems can provide very high data rates for short-range wireless communications. In part, UWB systems are designed to distribute information in home, office, school, and industrial environments using high-speed links between computer devices.
However, it is a challenge to realize UWB modulation schemes that increase data throughput while minimizing errors in dense multi-path environments. Propagation measurements and channel modeling studies indicate that many multi-path components (MPCs) are expected for an UWB radio link. In a dense multi-path environment, the number of MPCs increases linearly with the bandwidth.
For example, a system with a 10 GHz bandwidth, operating in an environment with a maximum excess delay spread of 100 ns requires a thousand fingers in a rake receiver. Even in a sparse multi-path environment, like the channels specified by the IEEE 802.15.3a standard for channel models, up to 80 fingers are required to collect 80% of the available energy.
In order to collect most of the available energy from MPCs, while at the same time reducing the number of fingers in the rake receiver, it is desired to estimate the channel impulse response so that the correct reference waveforms for convolutions with the received signal at each rake finger can be determined.
The requirements for channel estimation in the IEEE 802.15.3a standard for data format are stringent. Data are to be transmitted in blocks of 8,000 bits. It is also assumed that the channel can change from block to block. Each block of data lasts only 0.1 ms. The typical speed of movement in an indoor environment is about 1 meter per second, so for a 10 GHz upper frequency limit, the maximum Doppler frequency is 30 Hz. Thus, the channel stays stationary for only 30 ms.
The impulse responses can last up to 200 ns, as can be seen in the Final Report and Order. Because sampling has to be done at a rate of about 10 G samples per second, this means that 2000 samples of the channel impulse response have to be evaluated. If data are transmitted in a constant stream, then is should be possible to exploit the correlation between channel realizations.
In the prior art, the channel impulse response and equalizer coefficient are usually estimated from a single pseudo-noise (PN) training sequence. However, other users and out-of-band interferers might be transmitting while the single training sequence is transmitted. Therefore, there is a need to suppress co-channel interferers. This can be done by spreading the training sequence.
A brute-force approach samples and A/D converts the measured impulse response at a speed of 10 G samples per second. In principle, the channel sounding requires only two microseconds, i.e., the length of the impulse response times a factor of 10 for the interference suppression, which is 200 symbol durations. This is much shorter than the duration of the data block, and thus is not a significant overhead. However, A/D converters that can process 10,000,000,000 samples per second are prohibitively expensive.
During the estimation period, while the single training sequence is transmitted, it is necessary to sample the received signal at a chip rate to find the delays and amplitudes of the received multi-path components. Because the number of MPCs is not yet known at this time, each possible resolvable delay, i.e., each chip period, must be estimated. For a 10 GHz system, that again means sampling and A/D converting at 10 G samples/s, which is prohibitively expensive.
Therefore, there is a need for method and system that can estimate the channel impulse response and equalizer coefficient at a lower cost without degrading performance.